Dysphagia Symptoms Contribute to Greater Care Partner Burden in Neurodegenerative Disease
Bibliographic record
Abstract
Purpose: Providing care for family members with neurodegenerative diseases entails significant physical and psychosocial costs, increasing caregiver burden. Limited research exists on the factors contributing to dysphagia-related burden, particularly across disease trajectories. This study aimed to (a) determine if dysphagia-related burden predicts general caregiver burden, (b) identify predictors of dysphagia-related burden, and (c) examine relationships between dysphagia severity, disease severity, and dysphagia-related burden. Method: Care partners ( N = 211; 80% female; M age = 60 ± 14 years) from clinics in Canada, New Zealand, and the United States participated. Care recipients included those with amyotrophic lateral sclerosis (ALS; n = 48), dementia ( n = 110), and Parkinson's disease (PD; n = 53). General burden was measured using the Zarit Burden Interview, while dysphagia-related burden was assessed via the Caregiver Assessment of Reported Experiences with Swallowing Difficulties. Multiple regression analyses examined predictors of general and dysphagia-related burden and their relationships to dysphagia and disease severity. Results: Higher general burden was associated with female caregivers (β = −.19, p = .05), higher education (β = .16, p = .03), caring for someone with dementia (β = .36, p = .01), and greater dysphagia-related burden (β = .33, p = .01). Predictors of dysphagia-related burden included working caregivers (β = .15, p = .01), increased dysphagia symptoms (β = .77, p < .01), and caring for individuals with ALS or dementia (vs. PD; β = −.16, p = .02). Dysphagia burden varied by disease severity and diet tolerance ( p < .01). Conclusions: Managing dysphagia independently contributes to caregiver burden, potentially increasing burnout and nonadherence to clinical recommendations. Early, proactive inquiry about dysphagia-related care partner burden and provision of support to minimize burden should be considered early in disease management. Supplemental Material: https://doi.org/10.23641/asha.28843055
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".